Lexicographic goal programming approach for portfolio optimization

This paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. the meanvariance model of portfolio optimization that was introduced by markowitz includes two objective functions;these two criteria, risk and return do not encompass all of the information about investment; information likeannual dividends, s&p star ranking and return in later years which is estimated by using data from a longerhistory. thus portfolio selection is a typical multi-objective decision making (modm) problem. it is wellknown that goal programming (gp), based on preemptive priorities and target values, has been successful insolving modm problems. in this paper we rank objectives of the modm model according to weights elicitedfrom decision maker’s (dm) preferences. then we obtain goals from dm’s opinion. as a guidance for dm,we revise these goals consistent with ranking of objectives by a linear programming model in a way that newgoals remain as close as possible to dm’s goals. after obtaining the goals we solve our modm problem by alexicographic goal programming (lgp) model which is constructed by prioritizing objectives. finally we illustrateour proposed lgp model by a numerical example.